Search ga_ls7e_ard_3 across May 2017

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2017-05-11 09:48:53	ga_ls7e_ard_3-0-0_095072_2017-05-11_final
2017-05-11 09:49:17	ga_ls7e_ard_3-1-0_095073_2017-05-11_final
2017-05-11 09:49:41	ga_ls7e_ard_3-0-0_095074_2017-05-11_final
2017-05-11 09:50:05	ga_ls7e_ard_3-0-0_095075_2017-05-11_final
2017-05-11 09:50:29	ga_ls7e_ard_3-0-0_095076_2017-05-11_final
2017-05-11 09:50:52	ga_ls7e_ard_3-0-0_095077_2017-05-11_final
2017-05-13 09:37:19	ga_ls7e_ard_3-0-0_093074_2017-05-13_final
2017-05-13 09:37:43	ga_ls7e_ard_3-0-0_093075_2017-05-13_final
2017-05-13 09:38:55	ga_ls7e_ard_3-0-0_093078_2017-05-13_final
2017-05-13 09:39:19	ga_ls7e_ard_3-0-0_093079_2017-05-13_final
2017-05-13 09:39:43	ga_ls7e_ard_3-0-0_093080_2017-05-13_final
2017-05-13 09:40:07	ga_ls7e_ard_3-0-0_093081_2017-05-13_final
2017-05-13 09:40:31	ga_ls7e_ard_3-0-0_093082_2017-05-13_final
2017-05-13 09:40:55	ga_ls7e_ard_3-1-0_093083_2017-05-13_final
2017-05-13 09:41:19	ga_ls7e_ard_3-0-0_093084_2017-05-13_final
2017-05-13 09:41:43	ga_ls7e_ard_3-0-0_093085_2017-05-13_final
2017-05-13 09:42:07	ga_ls7e_ard_3-0-0_093086_2017-05-13_final
2017-05-13 09:42:31	ga_ls7e_ard_3-0-0_093087_2017-05-13_final
2017-05-13 09:42:55	ga_ls7e_ard_3-0-0_093088_2017-05-13_final
2017-05-23 10:11:38	ga_ls7e_ard_3-0-0_099067_2017-05-23_final
2017-05-23 10:12:02	ga_ls7e_ard_3-0-0_099068_2017-05-23_final
2017-05-23 10:12:26	ga_ls7e_ard_3-0-0_099069_2017-05-23_final
2017-05-23 10:12:50	ga_ls7e_ard_3-0-0_099070_2017-05-23_final
2017-05-23 10:13:14	ga_ls7e_ard_3-0-0_099071_2017-05-23_final
2017-05-23 10:13:38	ga_ls7e_ard_3-0-0_099072_2017-05-23_final
2017-05-23 10:14:02	ga_ls7e_ard_3-0-0_099073_2017-05-23_final
2017-05-23 10:14:26	ga_ls7e_ard_3-0-0_099074_2017-05-23_final
2017-05-23 10:14:49	ga_ls7e_ard_3-0-0_099075_2017-05-23_final
2017-05-23 10:15:13	ga_ls7e_ard_3-0-0_099076_2017-05-23_final
2017-05-23 10:15:37	ga_ls7e_ard_3-0-0_099077_2017-05-23_final
2017-05-23 10:16:01	ga_ls7e_ard_3-0-0_099078_2017-05-23_final
2017-05-23 10:16:25	ga_ls7e_ard_3-0-0_099079_2017-05-23_final
2017-05-23 10:16:49	ga_ls7e_ard_3-0-0_099080_2017-05-23_final
2017-05-23 10:17:13	ga_ls7e_ard_3-0-0_099081_2017-05-23_final
2017-05-23 10:17:37	ga_ls7e_ard_3-0-0_099082_2017-05-23_final
2017-05-23 10:18:01	ga_ls7e_ard_3-0-0_099083_2017-05-23_final
2017-05-23 10:18:25	ga_ls7e_ard_3-0-0_099084_2017-05-23_final
2017-05-23 11:53:19	ga_ls7e_ard_3-0-0_115074_2017-05-23_final
2017-05-23 11:53:43	ga_ls7e_ard_3-0-0_115075_2017-05-23_final
2017-05-23 11:54:06	ga_ls7e_ard_3-0-0_115076_2017-05-23_final
2017-05-23 11:54:30	ga_ls7e_ard_3-0-0_115077_2017-05-23_final
2017-05-23 11:54:54	ga_ls7e_ard_3-0-0_115078_2017-05-23_final
2017-05-23 11:55:18	ga_ls7e_ard_3-0-0_115079_2017-05-23_final
2017-05-24 09:20:00	ga_ls7e_ard_3-0-0_090077_2017-05-23_final
2017-05-24 09:20:24	ga_ls7e_ard_3-0-0_090078_2017-05-23_final
2017-05-24 09:20:48	ga_ls7e_ard_3-0-0_090079_2017-05-23_final
2017-05-24 09:21:12	ga_ls7e_ard_3-0-0_090080_2017-05-23_final
2017-05-24 09:21:36	ga_ls7e_ard_3-0-0_090081_2017-05-23_final
2017-05-24 09:22:00	ga_ls7e_ard_3-0-0_090082_2017-05-23_final
2017-05-24 09:22:24	ga_ls7e_ard_3-0-0_090083_2017-05-23_final
2017-05-24 09:22:48	ga_ls7e_ard_3-0-0_090084_2017-05-23_final
2017-05-24 09:23:12	ga_ls7e_ard_3-0-0_090085_2017-05-23_final
2017-05-24 09:23:36	ga_ls7e_ard_3-0-0_090086_2017-05-23_final
2017-05-24 09:24:24	ga_ls7e_ard_3-0-0_090088_2017-05-23_final
2017-05-24 09:24:48	ga_ls7e_ard_3-0-0_090089_2017-05-23_final
2017-05-24 09:25:12	ga_ls7e_ard_3-0-0_090090_2017-05-23_final
2017-05-24 10:55:18	ga_ls7e_ard_3-0-0_106068_2017-05-24_final
2017-05-24 10:55:42	ga_ls7e_ard_3-0-0_106069_2017-05-24_final
2017-05-24 10:56:06	ga_ls7e_ard_3-0-0_106070_2017-05-24_final
2017-05-24 10:56:30	ga_ls7e_ard_3-0-0_106071_2017-05-24_final
2017-05-24 10:56:54	ga_ls7e_ard_3-0-0_106072_2017-05-24_final
2017-05-24 10:57:17	ga_ls7e_ard_3-0-0_106073_2017-05-24_final
2017-05-24 10:57:41	ga_ls7e_ard_3-0-0_106074_2017-05-24_final
2017-05-24 10:58:05	ga_ls7e_ard_3-1-0_106075_2017-05-24_final
2017-05-24 10:58:29	ga_ls7e_ard_3-0-0_106076_2017-05-24_final
2017-05-24 10:58:53	ga_ls7e_ard_3-0-0_106077_2017-05-24_final
2017-05-24 10:59:17	ga_ls7e_ard_3-0-0_106078_2017-05-24_final
2017-05-24 10:59:41	ga_ls7e_ard_3-0-0_106079_2017-05-24_final
2017-05-24 11:00:05	ga_ls7e_ard_3-0-0_106080_2017-05-24_final
2017-05-24 11:00:29	ga_ls7e_ard_3-0-0_106081_2017-05-24_final
2017-05-24 11:00:53	ga_ls7e_ard_3-0-0_106082_2017-05-24_final
2017-05-24 11:01:17	ga_ls7e_ard_3-0-0_106083_2017-05-24_final
2017-05-25 10:00:05	ga_ls7e_ard_3-0-0_097069_2017-05-25_final
2017-05-25 10:00:29	ga_ls7e_ard_3-0-0_097070_2017-05-25_final
2017-05-25 10:00:53	ga_ls7e_ard_3-0-0_097071_2017-05-25_final
2017-05-25 10:01:17	ga_ls7e_ard_3-0-0_097072_2017-05-25_final
2017-05-25 10:01:41	ga_ls7e_ard_3-0-0_097073_2017-05-25_final
2017-05-25 10:02:04	ga_ls7e_ard_3-0-0_097074_2017-05-25_final
2017-05-25 10:02:28	ga_ls7e_ard_3-0-0_097075_2017-05-25_final
2017-05-25 10:02:52	ga_ls7e_ard_3-1-0_097076_2017-05-25_final
2017-05-25 10:03:16	ga_ls7e_ard_3-0-0_097077_2017-05-25_final
2017-05-25 10:03:40	ga_ls7e_ard_3-0-0_097078_2017-05-25_final
2017-05-25 10:04:04	ga_ls7e_ard_3-0-0_097079_2017-05-25_final
2017-05-25 10:04:28	ga_ls7e_ard_3-0-0_097080_2017-05-25_final
2017-05-25 10:04:52	ga_ls7e_ard_3-0-0_097081_2017-05-25_final
2017-05-25 10:05:16	ga_ls7e_ard_3-0-0_097082_2017-05-25_final
2017-05-25 10:05:40	ga_ls7e_ard_3-0-0_097083_2017-05-25_final
2017-05-25 10:06:04	ga_ls7e_ard_3-0-0_097084_2017-05-25_final
2017-05-25 10:06:28	ga_ls7e_ard_3-0-0_097085_2017-05-25_final
2017-05-25 11:38:10	ga_ls7e_ard_3-0-0_113067_2017-05-25_final
2017-05-25 11:40:58	ga_ls7e_ard_3-0-0_113074_2017-05-25_final
2017-05-25 11:41:21	ga_ls7e_ard_3-0-0_113075_2017-05-25_final
2017-05-25 11:41:45	ga_ls7e_ard_3-0-0_113076_2017-05-25_final
2017-05-25 11:42:09	ga_ls7e_ard_3-0-0_113077_2017-05-25_final
2017-05-25 11:42:33	ga_ls7e_ard_3-0-0_113078_2017-05-25_final
2017-05-25 11:42:57	ga_ls7e_ard_3-0-0_113079_2017-05-25_final
2017-05-25 11:43:21	ga_ls7e_ard_3-0-0_113080_2017-05-25_final
2017-05-25 11:43:45	ga_ls7e_ard_3-0-0_113081_2017-05-25_final
2017-05-25 11:44:09	ga_ls7e_ard_3-0-0_113082_2017-05-25_final
2017-05-25 11:44:33	ga_ls7e_ard_3-0-0_113083_2017-05-25_final

Return to ga_ls7e_ard_3 across May 2017 overview

ga_ls7e_ard_3: Geoscience Australia Landsat 7 Enhanced Thematic Mapper Plus Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

2017

May

All days